Road traffic sensor networks have been widely used as a source for traffic investigation and analysis. For example, vehicle data from these sensor networks have been used to detect traffic congestion and real-time traffic flow monitoring. Sensor networks may include sensor stations for detecting vehicles. The sensor stations, for example, may be sparsely distributed within the networks. The sparsity of the sensor stations may be due to cost or other constraints. The sparsity of the sensor stations practically make it impossible to determine detailed information on traveling behaviour within two consecutive stations along a vehicle's trajectory.
There may be instances where detailed information or behaviour of a vehicle between two consecutive sensor stations may be of interest. For example, identifying parking locations of a vehicle between two stations may be of interest such as in the case of locating an individual associated with the vehicle. However, such identification is practically impossible due to sparsity of sensor stations.
From the foregoing discussion, it is desirable to determine travel behaviour of a vehicle between two sensor stations such as parking areas.